- This course introduces some of the basic ideas of theoretical statistics, emphasizing the applications of these methods and the interpretation of tables and results.
- We will introduce concepts and methods that provide the foundation for more specialized courses in statistics.
- Students will be able to routinely apply a variety of methods for explaining, summarising, and presenting data and interpreting results clearly using appropriate diagrams, titles, and labels when required.
- Students will be able to summarise the ideas of randomness and variability and the way in which these link to probability theory to allow the systematic and logical collection of statistical techniques of great practical importance in many applied areas.
- Students will have a grounding in probability theory and some grasp of the most common statistical methods.
- Students will be able to recall a large number of distributions and be a competent user of their mass/density and distribution functions and moment generating functions.
- Students will be able to perform inference to test the significance of common measures such as means and proportions and conduct chi-squared tests of contingency tables.
- Students will be able to use simple linear regression and correlation analysis and know when it is appropriate to do so.
- Data presentation.
- Elements of probability theory.
- Discrete random variables.
- Continuous random variables.
- Multivariate random variables.
- Conditional distributions.
- Interim assessment (1 semester)0.2 * Final Project + 0.1 * Programming + 0.4 * Quizzes + 0.3 * SGA